(An image from Xavi Bou’s project Ornitographies.)
Have you ever found bird flocks mesmerizing? I certainly do. But did you know that it’s not the birds that memorize, but the flock itself? This behavior arises from simple rules and interactions. It’s fascinating how a system with simple components and rules can create something incredibly complex and sophisticated. I find this theme absolutely captivating and wanted to share it with you.
To form a flock with morphing patterns, each bird follows simple rules based on its neighbors, yet together they create stunning, coordinated patterns. There’s no leader, no master plan, just simple interactions creating beautiful complexity. Now, think about financial markets: Individual traders, each making decisions based on personal goals and available information, collectively create market trends, bubbles, and crashes. It’s not that any one trader is orchestrating these large-scale phenomena, but their combined actions lead to the complex behavior we observe in the market.
The concept of emergency is also deeply connected to the latest buzz in town: AI, especially with large language models (LLMs) like OpenAI’s GPT series. These models are based on fundamental principles of neural networks and machine learning algorithms. However, as the size of these models increases, they are able to comprehend and generate human-like text, engage in complex reasoning, and produce original content. These advanced capabilities are a result of the interaction of many simple processing units, which frequently leads to astonishing results - often causing us to overlook the fundamental nature underlying all of this.
If we break intelligence down to its core, it contains three parts: the ability to learn, the ability to adapt, and the ability to solve problems. All of these can be achieved by simple rules. The ability to learn has been shown to be achievable by backpropagation and gradient descent. Adaptation can be achieved by evolutionary processes such as random mutation and survival of the fittest. Problem-solving can be achieved by swarm intelligence methods such as cellular automata.
The beauty of emergence lies in its simplicity. It shows us that even basic interactions can lead to profound outcomes. This idea applies across nature, technology, and our own thought processes. One implication that excites me the most is that we should not be daunted by the complexity or emergent capabilities themselves. What we should be paying attention to are their fundamental units - studying and understanding them helps us learn and leverage much bigger and more complex systems in the ever-changing world.
If you enjoyed this exploration of emergence, you might like Complextropy and Complexodynamics - where sophistication peaks between order and chaos.